Advancing functional and translational microbiome research using meta-omics approaches

An integrated metaproteomics workflow for studying host-microbe dynamics in bronchoalveolar lavage samples applied to cystic fibrosis disease

Airway microbiota are known to contribute to lung diseases, such as cystic fibrosis (CF), but their contributions to pathogenesis are still unclear. To improve our understanding of host-microbe interactions, we have developed an integrated analytical and bioinformatic mass spectrometry (MS)-based metaproteomics workflow to analyze clinical bronchoalveolar lavage (BAL) samples from people with airway disease. Proteins from BAL cellular pellets were processed and pooled together in groups categorized by disease status (CF vs. non-CF) and bacterial diversity, based on previously performed small subunit rRNA sequencing data. Proteins from each pooled sample group were digested and subjected to liquid chromatography tandem mass spectrometry (MS/MS). MS/MS spectra were matched to human and bacterial peptide sequences leveraging a bioinformatic workflow using a metagenomics-guided protein sequence database and rigorous evaluation. Label-free quantification revealed differentially abundant human peptides from proteins with known roles in CF, like neutrophil elastase and collagenase, and proteins with lesser-known roles in CF, including apolipoproteins. Differentially abundant bacterial peptides were identified from known CF pathogens (e.g., Pseudomonas), as well as other taxa with potentially novel roles in CF. We used this host-microbe peptide panel for targeted parallel-reaction monitoring validation, demonstrating for the first time an MS-based assay effective for quantifying host-microbe protein dynamics within BAL cells from individual CF patients. Our integrated bioinformatic and analytical workflow combining discovery, verification, and validation should prove useful for diverse studies to characterize microbial contributors in airway diseases. Furthermore, we describe a promising preliminary panel of differentially abundant microbe and host peptide sequences for further study as potential markers of host-microbe relationships in CF disease pathogenesis.IMPORTANCEIdentifying microbial pathogenic contributors and dysregulated human responses in airway disease, such as CF, is critical to understanding disease progression and developing more effective treatments. To this end, characterizing the proteins expressed from bacterial microbes and human host cells during disease progression can provide valuable new insights. We describe here a new method to confidently detect and monitor abundance changes of both microbe and host proteins from challenging BAL samples commonly collected from CF patients. Our method uses both state-of-the art mass spectrometry-based instrumentation to detect proteins present in these samples and customized bioinformatic software tools to analyze the data and characterize detected proteins and their association with CF. We demonstrate the use of this method to characterize microbe and host proteins from individual BAL samples, paving the way for a new approach to understand molecular contributors to CF and other diseases of the airway.

A novel clinical metaproteomics workflow enables bioinformatic analysis of host-microbe dynamics in disease

Clinical metaproteomics has the potential to offer insights into the host-microbiome interactions underlying diseases. However, the field faces challenges in characterizing microbial proteins found in clinical samples, usually present at low abundance relative to the host proteins. As a solution, we have developed an integrated workflow coupling mass spectrometry-based analysis with customized bioinformatic identification, quantification, and prioritization of microbial proteins, enabling targeted assay development to investigate host-microbe dynamics in disease. The bioinformatics tools are implemented in the Galaxy ecosystem, offering the development and dissemination of complex bioinformatic workflows. The modular workflow integrates MetaNovo (to generate a reduced protein database), SearchGUI/PeptideShaker and MaxQuant [to generate peptide-spectral matches (PSMs) and quantification], PepQuery2 (to verify the quality of PSMs), Unipept (for taxonomic and functional annotation), and MSstatsTMT (for statistical analysis). We have utilized this workflow in diverse clinical samples, from the characterization of nasopharyngeal swab samples to bronchoalveolar lavage fluid. Here, we demonstrate its effectiveness via analysis of residual fluid from cervical swabs. The complete workflow, including training data and documentation, is available via the Galaxy Training Network, empowering non-expert researchers to utilize these powerful tools in their clinical studies.

IMPORTANCE

Clinical metaproteomics has immense potential to offer functional insights into the microbiome and its contributions to human disease. However, there are numerous challenges in the metaproteomic analysis of clinical samples, including handling of very large protein sequence databases for sensitive and accurate peptide and protein identification from mass spectrometry data, as well as taxonomic and functional annotation of quantified peptides and proteins to enable interpretation of results. To address these challenges, we have developed a novel clinical metaproteomics workflow that provides customized bioinformatic identification, verification, quantification, and taxonomic and functional annotation. This bioinformatic workflow is implemented in the Galaxy ecosystem and has been used to characterize diverse clinical sample types, such as nasopharyngeal swabs and bronchoalveolar lavage fluid. Here, we demonstrate its effectiveness and availability for use by the research community via analysis of residual fluid from cervical swabs.

Gut microbiota-derived acetate attenuates lung injury induced by influenza infection via protecting airway tight junctions

BACKGROUND

Gut microbiota (GM) have been implicated as important regulators of gastrointestinal symptom which is commonly occurred along with respiratory influenza A virus (IAV) infection, suggesting the involvement of the gut-to-lung axis in a host's response to IAV. IAV primarily destroys airway epithelium tight junctions (TJs) and consequently causes acute respiratory disease syndrome. It is known that GM and their metabolism produce an anti-influenza effect, but their role in IAV-induced airway epithelial integrity remains unknown.

METHODS

A mouse model of IAV infection was established. GM were analyzed using 16S rRNA gene sequencing, and short-chain fatty acids (SCFAs) levels were measured. GM depletion and fecal microbiota transplantation (FMT) were conducted to validate the role of GM in IAV infection. A pair-feeding experiment was conducted to reveal whether IAV-induced GM dysbiosis is attributed to impaired food intake. Furthermore, human bronchial epithelial (HBE) cells were cocultured with IAV in the presence or absence of acetate. TJs function was analyzed by paracellular permeability and transepithelial electronic resistance (TEER). The mechanism of how acetate affects TJs integrity was evaluated in HBE cells transfected with G protein-coupled receptor 43 (GPR43) short hairpin RNA (shRNA).

RESULTS

IAV-infected mice exhibited lower relative abundance of acetate-producing bacteria (Bacteroides, Bifidobacterium, and Akkermansia) and decreased acetate levels in gut and serum. These changes were partly caused by a decrease in food consumption (due to anorexia). GM depletion exacerbated and FMT restored IAV-induced lung inflammatory injury. IAV infection suppressed expressions of TJs (occludin, ZO-1) leading to disrupted airway epithelial barrier function as evidenced by decreased TEER and increased permeability. Acetate pretreatment activated GPR43, partially restored IAV-induced airway epithelial barrier function, and reduced inflammatory cytokines levels (TNF-α, IL-6, and IL-1β). Such protective effects of acetate were absent in HBE cells transfected with GPR43 shRNA. Acetate and GPR43 improved TJs in an AMP-activated protein kinase (AMPK)-dependent manner.

CONCLUSION

Collectively, our results demonstrated that GM protected airway TJs by modulating GPR43-AMPK signaling in IAV-induced lung injury. Therefore, improving GM dysbiosis may be a potential therapeutic target for patients with IAV infection.

Advances in the isolation, cultivation, and identification of gut microbes

The gut microbiome is closely associated with human health and the development of diseases. Isolating, characterizing, and identifying gut microbes are crucial for research on the gut microbiome and essential for advancing our understanding and utilization of it. Although culture-independent approaches have been developed, a pure culture is required for in-depth analysis of disease mechanisms and the development of biotherapy strategies. Currently, microbiome research faces the challenge of expanding the existing database of culturable gut microbiota and rapidly isolating target microorganisms. This review examines the advancements in gut microbe isolation and cultivation techniques, such as culturomics, droplet microfluidics, phenotypic and genomics selection, and membrane diffusion. Furthermore, we evaluate the progress made in technology for identifying gut microbes considering both non-targeted and targeted strategies. The focus of future research in gut microbial culturomics is expected to be on high-throughput, automation, and integration. Advancements in this field may facilitate strain-level investigation into the mechanisms underlying diseases related to gut microbiota.

A complementary metaproteomic approach to interrogate microbiome cultivated from clinical colon biopsies

The human gut microbiome plays a vital role in preserving individual health and is intricately involved in essential functions. Imbalances or dysbiosis within the microbiome can significantly impact human health and are associated with many diseases. Several metaproteomics platforms are currently available to study microbial proteins within complex microbial communities. In this study, we attempted to develop an integrated pipeline to provide deeper insights into both the taxonomic and functional aspects of the cultivated human gut microbiomes derived from clinical colon biopsies. We combined a rapid peptide search by MSFragger against the Unified Human Gastrointestinal Protein database and the taxonomic and functional analyses with Unipept Desktop and MetaLab-MAG. Across seven samples, we identified and matched nearly 36,000 unique peptides to approximately 300 species and 11 phyla. Unipept Desktop provided gene ontology, InterPro entries, and enzyme commission number annotations, facilitating the identification of relevant metabolic pathways. MetaLab-MAG contributed functional annotations through Clusters of Orthologous Genes and Non-supervised Orthologous Groups categories. These results unveiled functional similarities and differences among the samples. This integrated pipeline holds the potential to provide deeper insights into the taxonomy and functions of the human gut microbiome for interrogating the intricate connections between microbiome balance and diseases.

The Role and Applications of Artificial Intelligence in the Treatment of Chronic Pain

PURPOSE OF REVIEW

This review aims to explore the interface between artificial intelligence (AI) and chronic pain, seeking to identify areas of focus for enhancing current treatments and yielding novel therapies.

RECENT FINDINGS

In the United States, the prevalence of chronic pain is estimated to be upwards of 40%. Its impact extends to increased healthcare costs, reduced economic productivity, and strain on healthcare resources. Addressing this condition is particularly challenging due to its complexity and the significant variability in how patients respond to treatment. Current options often struggle to provide long-term relief, with their benefits rarely outweighing the risks, such as dependency or other side effects. Currently, AI has impacted four key areas of chronic pain treatment and research: (1) predicting outcomes based on clinical information; (2) extracting features from text, specifically clinical notes; (3) modeling 'omic data to identify meaningful patient subgroups with potential for personalized treatments and improved understanding of disease processes; and (4) disentangling complex neuronal signals responsible for pain, which current therapies attempt to modulate. As AI advances, leveraging state-of-the-art architectures will be essential for improving chronic pain treatment. Current efforts aim to extract meaningful representations from complex data, paving the way for personalized medicine. The identification of unique patient subgroups should reveal targets for tailored chronic pain treatments. Moreover, enhancing current treatment approaches is achievable by gaining a more profound understanding of patient physiology and responses. This can be realized by leveraging AI on the increasing volume of data linked to chronic pain.

Fine-tuning the gut ecosystem: the current landscape and outlook of artificial microbiome therapeutics

The gut microbiome is acknowledged as a key determinant of human health, and technological progress in the past two decades has enabled the deciphering of its composition and functions and its role in human disorders. Therefore, manipulation of the gut microbiome has emerged as a promising therapeutic option for communicable and non-communicable disorders. Full exploitation of current therapeutic microbiome modulators (including probiotics, prebiotics, and faecal microbiota transplantation) is hindered by several factors, including poor precision, regulatory and safety issues, and the impossibility of providing reproducible and targeted treatments. Artificial microbiota therapeutics (which include a wide range of products, such as microbiota consortia, bacteriophages, bacterial metabolites, and engineered probiotics) have appeared as an evolution of current microbiota modulators, as they promise safe and reproducible effects, with variable levels of precision via different pathways. We describe the landscape of artificial microbiome therapeutics, from those already on the market to those still in the pipeline, and outline the major challenges for positioning these therapeutics in clinical practice.

Anaerostipes hadrus, a butyrate-producing bacterium capable of metabolizing 5-fluorouracil

Anaerostipes hadrus (A. hadrus) is a dominant species in the human gut microbiota and considered a beneficial bacterium for producing probiotic butyrate. However, recent studies have suggested that A. hadrus may negatively affect the host through synthesizing fatty acid and metabolizing the anticancer drug 5-fluorouracil, indicating that the impact of A. hadrus is complex and unclear. Therefore, comprehensive genomic studies on A. hadrus need to be performed. We integrated 527 high-quality public A. hadrus genomes and five distinct metagenomic cohorts. We analyzed these data using the approaches of comparative genomics, metagenomics, and protein structure prediction. We also performed validations with culture-based in vitro assays. We constructed the first large-scale pan-genome of A. hadrus (n = 527) and identified 5-fluorouracil metabolism genes as ubiquitous in A. hadrus genomes as butyrate-producing genes. Metagenomic analysis revealed the wide and stable distribution of A. hadrus in healthy individuals, patients with inflammatory bowel disease, and patients with colorectal cancer, with healthy individuals carrying more A. hadrus. The predicted high-quality protein structure indicated that A. hadrus might metabolize 5-fluorouracil by producing bacterial dihydropyrimidine dehydrogenase (encoded by the preTA operon). Through in vitro assays, we validated the short-chain fatty acid production and 5-fluorouracil metabolism abilities of A. hadrus. We observed for the first time that A. hadrus can convert 5-fluorouracil to α-fluoro-β-ureidopropionic acid, which may result from the combined action of the preTA operon and adjacent hydA (encoding bacterial dihydropyrimidinase). Our results offer novel understandings of A. hadrus, exceptionally functional features, and potential applications.

IMPORTANCE

This work provides new insights into the evolutionary relationships, functional characteristics, prevalence, and potential applications of Anaerostipes hadrus.

Multiomics data integration, limitations, and prospects to reveal the metabolic activity of the coral holobiont

Since their radiation in the Middle Triassic period ∼240 million years ago, stony corals have survived past climate fluctuations and five mass extinctions. Their long-term survival underscores the inherent resilience of corals, particularly when considering the nutrient-poor marine environments in which they have thrived. However, coral bleaching has emerged as a global threat to coral survival, requiring rapid advancements in coral research to understand holobiont stress responses and allow for interventions before extensive bleaching occurs. This review encompasses the potential, as well as the limits, of multiomics data applications when applied to the coral holobiont. Synopses for how different omics tools have been applied to date and their current restrictions are discussed, in addition to ways these restrictions may be overcome, such as recruiting new technology to studies, utilizing novel bioinformatics approaches, and generally integrating omics data. Lastly, this review presents considerations for the design of holobiont multiomics studies to support lab-to-field advancements of coral stress marker monitoring systems. Although much of the bleaching mechanism has eluded investigation to date, multiomic studies have already produced key findings regarding the holobiont's stress response, and have the potential to advance the field further.

Proteomic scrutiny of nasal microbiomes: implications for the clinic

INTRODUCTION

The nasal cavity is the initial site of the human respiratory tract and is one of the habitats where microorganisms colonize. The findings from a growing number of studies have shown that the nasal microbiome is an important factor for human disease and health. 16S rRNA sequencing and metagenomic next-generation sequencing (mNGS) are the most commonly used means of microbiome evaluation. Among them, 16S rRNA sequencing is the primary method used in previous studies of nasal microbiomes. However, neither 16S rRNA sequencing nor mNGS can be used to analyze the genes specifically expressed by nasal microorganisms and their functions. This problem can be addressed by proteomic analysis of the nasal microbiome.

AREAS COVERED

In this review, we summarize current advances in research on the nasal microbiome, introduce the methods for proteomic evaluation of the nasal microbiome, and focus on the important roles of proteomic evaluation of the nasal microbiome in the diagnosis and treatment of related diseases.

EXPERT OPINION

The detection method for microbiome-expressed proteins is known as metaproteomics. Metaproteomic analysis can help us dig deeper into the nasal microbiomes and provide new targets and ideas for clinical diagnosis and treatment of many nasal dysbiosis-related diseases.

Microbiome and lung cancer: carcinogenic mechanisms, early cancer diagnosis, and promising microbial therapies

Microbiomes in the lung, gut, and oral cavity are correlated with lung cancer initiation and progression. While correlations have been preliminarily established in earlier studies, delving into microbe-mediated carcinogenic mechanisms will extend our understanding from correlation to causation. Building upon the causative relationships between microbiome and lung cancer, a novel concept of microbial biomarkers has emerged, mainly encompassing cancer-specific bacteria and circulating microbiome DNA. They might function as noninvasive liquid biopsy techniques for lung cancer early detection. Furthermore, potential microbial therapies have displayed initial efficacy in lung cancer treatment, providing multiple avenues for therapeutic intervention. Herein, we will discuss the molecular mechanisms and signaling pathways through which microbes influence lung cancer initiation and development. Additionally, we will summarize recent findings on microbial biomarkers as a member of tumor liquid biopsy techniques and provide an overview of the latest advances in various microbe-assisted/mediated therapeutic approaches for lung cancer.

Bisphenol A exposure affects specific gut taxa and drives microbiota dynamics in childhood obesity

Cumulative xenobiotic exposure has an environmental and human health impact which is currently assessed under the One Health approach. Bisphenol A (BPA) exposure and its potential link with childhood obesity that has parallelly increased during the last decades deserve special attention. It stands during prenatal or early life and could trigger comorbidities and non-communicable diseases along life. Accumulation in the nature of synthetic chemicals supports the "environmental obesogen" hypothesis, such as BPA. This estrogen-mimicking xenobiotic has shown endocrine disruptive and obesogenic effects accompanied by gut microbiota misbalance that is not yet well elucidated. This study aimed to investigate specific microbiota taxa isolated and selected by direct BPA exposure and reveal its role on the overall children microbiota community and dynamics, driving toward specific obesity dysbiosis. A total of 333 BPA-resistant isolated species obtained through culturing after several exposure conditions were evaluated for their role and interplay with the global microbial community. The selected BPA-cultured taxa biomarkers showed a significant impact on alpha diversity. Specifically, Clostridium and Romboutsia were positively associated promoting the richness of microbiota communities, while Intestinibacter, Escherichia-Shigella, Bifidobacterium, and Lactobacillus were negatively associated. Microbial community dynamics and networks analyses showed differences according to the study groups. The normal-weight children group exhibited a more enriched, structured, and connected taxa network compared to overweight and obese groups, which could represent a more resilient community to xenobiotic substances. In this sense, subnetwork analysis generated with the BPA-cultured genera showed a correlation between taxa connectivity and more diverse potential enzymatic BPA degradation capacities.IMPORTANCEOur findings indicate how gut microbiota taxa with the capacity to grow in BPA were differentially represented within differential body mass index children study groups and how these taxa affected the overall dynamics toward patterns of diversity generally recognized in dysbiosis. Community network and subnetwork analyses corroborated the better connectedness and stability profiles for normal-weight group compared to the overweight and obese groups.

Metabolites: a converging node of host and microbe to explain meta-organism

Meta-organisms encompassing the host and resident microbiota play a significant role in combatting diseases and responding to stress. Hence, there is growing traction to build a knowledge base about this ecosystem, particularly to characterize the bidirectional relationship between the host and microbiota. In this context, metabolomics has emerged as the major converging node of this entire ecosystem. Systematic comprehension of this resourceful omics component can elucidate the organism-specific response trajectory and the communication grid across the ecosystem embodying meta-organisms. Translating this knowledge into designing nutraceuticals and next-generation therapy are ongoing. Its major hindrance is a significant knowledge gap about the underlying mechanisms maintaining a delicate balance within this ecosystem. To bridge this knowledge gap, a holistic picture of the available information has been presented with a primary focus on the microbiota-metabolite relationship dynamics. The central theme of this article is the gut-brain axis and the participating microbial metabolites that impact cerebral functions.

Novel Techniques and Models for Studying the Role of the Gut Microbiota in Drug Metabolism

The gut microbiota, known as the second human genome, plays a vital role in modulating drug metabolism, significantly impacting therapeutic outcomes and adverse effects. Emerging research has elucidated that the microbiota mediates a range of modifications of drugs, leading to their activation, inactivation, or even toxication. In diverse individuals, variations in the gut microbiota can result in differences in microbe-drug interactions, underscoring the importance of personalized approaches in pharmacotherapy. However, previous studies on drug metabolism in the gut microbiota have been hampered by technical limitations. Nowadays, advances in biotechnological tools, such as microbially derived metabolism screening and microbial gene editing, have provided a deeper insight into the mechanism of drug metabolism by gut microbiota, moving us toward personalized therapeutic interventions. Given this situation, our review summarizes recent advances in the study of gut-microbiota-mediated drug metabolism and showcases techniques and models developed to navigate the challenges posed by the microbial involvement in drug action. Therefore, we not only aim at understanding the complex interaction between the gut microbiota and drugs and outline the development of research techniques and models, but we also summarize the specific applications of new techniques and models in researching gut-microbiota-mediated drug metabolism, with the expectation of providing new insights on how to study drug metabolism by gut microbiota.

Metaproteomics analysis of anaerobic digestion of food waste by the addition of calcium peroxide and magnetite

Adding trace calcium peroxide and magnetite into a semi-continuous digester is a new method to effectively improve the anaerobic digestion of food waste. However, the microbial mechanism in this system has not been fully explored. Metaproteomics further revealed that the most active and significantly regulated genus u_p_Chloroflexi had formed a good cooperative relationship with Methanomicrobiales and Methanothrix in the system. u_p_Chloroflexi decomposed more organic compounds into CO2, acetate, amino acids, and other substances by alternating between short aerobic-anaerobic respiration. It perceived and adapted to the surrounding environment by producing biofilm, extracellular enzymes, and accelerating substrate transport, formed a respiratory barrier, and enhanced iron transport capacity by using highly expressed cytochrome C. The methanogens formed reactive oxygen species scavengers and reduced iron transport to prevent oxidative damage. This study provides new insight for improving the efficiency of anaerobic digestion of food waste and identifying key microorganisms and their regulated functional proteins in the calcium peroxide-magnetite digestion system.IMPORTANCEPrevious study has found that the combination of calcium peroxide and magnetite has a good promoting effect on the anaerobic digestion process of food waste. Through multiple omics approaches, information such as microbial population structure and changes in metabolites can be further analyzed. This study can help researchers gain a deeper understanding of the digestion pathway of food waste under the combined action of calcium peroxide and magnetite, further elucidate the impact mechanisms of calcium peroxide and magnetite at the microbial level, and provide theoretical guidance to improve the efficiency and stability of anaerobic digestion of food waste, as well as reduce operational costs. This research contributes to improving energy recovery efficiency, promoting sustainable management and development of food waste, and is of great significance to environmental protection.

Gut microbiome as a treatment in colorectal cancer

BACKGROUND

The gut microbiome plays a role in the development and progression of colorectal cancer (CRC).

AIM AND OBJECTIVE

This review focuses on whether the gut microbiome is involved in the development and regulation of the host immune system.

METHODS

The gut microbiome can influence the production and activity of immune cells and molecules that help to maintain the integrity of the intestinal barrier and prevent inflammation. Gut microbiota modulates the anti-cancer immune response. The gut microbiota can influence the function of immune cells, like T cells, that recognize and eliminate cancer cells. Gut microbiota can affect various aspects of cancer progression and the efficacy of various anti-cancer treatments.

RESULTS

Gut microbiota provide promise as a potential biomarker to identify the effect of immunotherapy and as a target for modulation to improve the efficacy of immunotherapy in CRC treatment.

CONCLUSION

The potential synergistic effect between the gut microbiome and anti-cancer treatment modalities provides an interest in developing strategies to modulate the gut microbiome to improve the efficacy of anti-cancer treatment.

From mechanism to application: Decrypting light-regulated denitrifying microbiome through geometric deep learning

Regulation on denitrifying microbiomes is crucial for sustainable industrial biotechnology and ecological nitrogen cycling. The holistic genetic profiles of microbiomes can be provided by meta-omics. However, precise decryption and further applications of highly complex microbiomes and corresponding meta-omics data sets remain great challenges. Here, we combined optogenetics and geometric deep learning to form a discover-model-learn-advance (DMLA) cycle for denitrification microbiome encryption and regulation. Graph neural networks (GNNs) exhibited superior performance in integrating biological knowledge and identifying coexpression gene panels, which could be utilized to predict unknown phenotypes, elucidate molecular biology mechanisms, and advance biotechnologies. Through the DMLA cycle, we discovered the wavelength-divergent secretion system and nitrate-superoxide coregulation, realizing increasing extracellular protein production by 83.8% and facilitating nitrate removal with 99.9% enhancement. Our study showcased the potential of GNNs-empowered optogenetic approaches for regulating denitrification and accelerating the mechanistic discovery of microbiomes for in-depth research and versatile applications.

Wekemo Bioincloud: A user-friendly platform for meta-omics data analyses

The increasing application of meta-omics approaches to investigate the structure, function, and intercellular interactions of microbial communities has led to a surge in available data. However, this abundance of human and environmental microbiome data has exposed new scalability challenges for existing bioinformatics tools. In response, we introduce Wekemo Bioincloud-a specialized platform for -omics studies. This platform offers a comprehensive analysis solution, specifically designed to alleviate the challenges of tool selection for users in the face of expanding data sets. As of now, Wekemo Bioincloud has been regularly equipped with 22 workflows and 65 visualization tools, establishing itself as a user-friendly and widely embraced platform for studying diverse data sets. Additionally, the platform enables the online modification of vector outputs, and the registration-independent personalized dashboard system ensures privacy and traceability. Wekemo Bioincloud is freely available at https://www.bioincloud.tech/.

Current insights into genome-based personalized nutrition technology: a patent review

Unlike general nutritional ranges that meet the nutritional needs essential for maintaining the life of an entire population, personalized nutrition is characterised by maintaining health through providing customized nutrition according to individuals' lifestyles or genetic characteristics. The development of technology and services for personalized nutrition is increasing, owing to the acquisition of knowledge about the differences in nutritional requirements according to the diversity of individuals and an increase in health interest. Regarding genetics, technology is being developed to distinguish the various characteristics of individuals and provide customized nutrition. Therefore, to understand the current state of personalized nutrition technology, understanding genomics is necessary to acquire information on nutrition research based on genomics. We reviewed patents related to personalized nutrition-targeting genomics and examined their mechanisms of action. Using the patent database, we searched 694 patents on nutritional genomics and extracted 561 highly relevant valid data points. Furthermore, an in-depth review was conducted by selecting core patents related to genome-based personalized nutrition technology. A marked increase was observed in personalized nutrition technologies using methods such as genetic scoring and disease-specific dietary recommendations.

Mock community taxonomic classification performance of publicly available shotgun metagenomics pipelines

Shotgun metagenomic sequencing comprehensively samples the DNA of a microbial sample. Choosing the best bioinformatics processing package can be daunting due to the wide variety of tools available. Here, we assessed publicly available shotgun metagenomics processing packages/pipelines including bioBakery, Just a Microbiology System (JAMS), Whole metaGenome Sequence Assembly V2 (WGSA2), and Woltka using 19 publicly available mock community samples and a set of five constructed pathogenic gut microbiome samples. Also included is a workflow for labelling bacterial scientific names with NCBI taxonomy identifiers for better resolution in assessing results. The Aitchison distance, a sensitivity metric, and total False Positive Relative Abundance were used for accuracy assessments for all pipelines and mock samples. Overall, bioBakery4 performed the best with most of the accuracy metrics, while JAMS and WGSA2, had the highest sensitivities. Furthermore, bioBakery is commonly used and only requires a basic knowledge of command line usage. This work provides an unbiased assessment of shotgun metagenomics packages and presents results assessing the performance of the packages using mock community sequence data.

An omics review and perspective of researches on intrahepatic cholestasis of pregnancy

Intrahepatic cholestasis of pregnancy (ICP) is one of the common pregnancy complications that may threaten the health of both pregnant women and their fetuses. Hence, it is of vital importance to identify key moleculars and the associated functional pathways of ICP, which will help us to better understand the pathological mechanisms as well as to develop precise clinical biomarkers. The emerging and developing of multiple omics approaches enable comprehensive studies of the genome, transcriptome, proteome and metabolome of clinical samples. The present review collected and summarized the omics based studies of ICP, aiming to provide an overview of the current progress, limitations and future directions. Briefly, these studies covered a broad range of research contents by the comparing of different experimental groups including ICP patients, ICP subtypes, ICP fetuses, ICP models and other complications. Correspondingly, the studied samples contain various types of clinical samples, in vitro cultured tissues, cell lines and the samples from animal models. According to the main research objectives, we further categorized these studies into two groups: pathogenesis and diagnosis analyses. The pathogenesis studies identified tens of functional pathways that may represent the key regulatory events for the occurrence, progression, treatment and fetal effects of ICP. On the other hand, the diagnosis studies tested more than 40 potential models for the early-prediction, diagnosis, grading, prognosis or differential diagnosis of ICP. Apart from these achievements, we also evaluated the limitations of current studies, and emphasized that many aspects of clinical characteristics, sample processing, and analytical method can greatly affect the reliability and repeatability of omics results. Finally, we also pointed out several new directions for the omics based analyses of ICP and other perinatal associated conditions in the future.

Community-scale models of microbiomes: Articulating metabolic modelling and metagenome sequencing

Building models is essential for understanding the functions and dynamics of microbial communities. Metabolic models built on genome-scale metabolic network reconstructions (GENREs) are especially relevant as a means to decipher the complex interactions occurring among species. Model reconstruction increasingly relies on metagenomics, which permits direct characterisation of naturally occurring communities that may contain organisms that cannot be isolated or cultured. In this review, we provide an overview of the field of metabolic modelling and its increasing reliance on and synergy with metagenomics and bioinformatics. We survey the means of assigning functions and reconstructing metabolic networks from (meta-)genomes, and present the variety and mathematical fundamentals of metabolic models that foster the understanding of microbial dynamics. We emphasise the characterisation of interactions and the scaling of model construction to large communities, two important bottlenecks in the applicability of these models. We give an overview of the current state of the art in metagenome sequencing and bioinformatics analysis, focusing on the reconstruction of genomes in microbial communities. Metagenomics benefits tremendously from third-generation sequencing, and we discuss the opportunities of long-read sequencing, strain-level characterisation and eukaryotic metagenomics. We aim at providing algorithmic and mathematical support, together with tool and application resources, that permit bridging the gap between metagenomics and metabolic modelling.

From hype to hope: Considerations in conducting robust microbiome science

Microbiome science has been one of the most exciting and rapidly evolving research fields in the past two decades. Breakthroughs in technologies including DNA sequencing have meant that the trillions of microbes (particularly bacteria) inhabiting human biological niches (particularly the gut) can be profiled and analysed in exquisite detail. This microbiome profiling has profound impacts across many fields of research, especially biomedical science, with implications for how we understand and ultimately treat a wide range of human disorders. However, like many great scientific frontiers in human history, the pioneering nature of microbiome research comes with a multitude of challenges and potential pitfalls. These include the reproducibility and robustness of microbiome science, especially in its applications to human health outcomes. In this article, we address the enormous promise of microbiome science and its many challenges, proposing constructive solutions to enhance the reproducibility and robustness of research in this nascent field. The optimisation of microbiome science spans research design, implementation and analysis, and we discuss specific aspects such as the importance of ecological principals and functionality, challenges with microbiome-modulating therapies and the consideration of confounding, alternative options for microbiome sequencing, and the potential of machine learning and computational science to advance the field. The power of microbiome science promises to revolutionise our understanding of many diseases and provide new approaches to prevention, early diagnosis, and treatment.

A novel clinical metaproteomics workflow enables bioinformatic analysis of host-microbe dynamics in disease

Clinical metaproteomics has the potential to offer insights into the host-microbiome interactions underlying diseases. However, the field faces challenges in characterizing microbial proteins found in clinical samples, which are usually present at low abundance relative to the host proteins. As a solution, we have developed an integrated workflow coupling mass spectrometry-based analysis with customized bioinformatic identification, quantification and prioritization of microbial and host proteins, enabling targeted assay development to investigate host-microbe dynamics in disease. The bioinformatics tools are implemented in the Galaxy ecosystem, offering the development and dissemination of complex bioinformatic workflows. The modular workflow integrates MetaNovo (to generate a reduced protein database), SearchGUI/PeptideShaker and MaxQuant (to generate peptide-spectral matches (PSMs) and quantification), PepQuery2 (to verify the quality of PSMs), and Unipept and MSstatsTMT (for taxonomy and functional annotation). We have utilized this workflow in diverse clinical samples, from the characterization of nasopharyngeal swab samples to bronchoalveolar lavage fluid. Here, we demonstrate its effectiveness via analysis of residual fluid from cervical swabs. The complete workflow, including training data and documentation, is available via the Galaxy Training Network, empowering non-expert researchers to utilize these powerful tools in their clinical studies.

Bridging the Gap from Enterotypes to Personalized Dietary Recommendations: A Metabolomics Perspective on Microbiome Research

Advances in high-throughput DNA sequencing have propelled research into the human microbiome and its link to metabolic health. We explore microbiome analysis methods, specifically emphasizing metabolomics, how dietary choices impact the production of microbial metabolites, providing an overview of studies examining the connection between enterotypes and diet, and thus, improvement of personalized dietary recommendations. Acetate, propionate, and butyrate constitute more than 95% of the collective pool of short-chain fatty acids. Conflicting data on acetate's effects may result from its dynamic signaling, which can vary depending on physiological conditions and metabolic phenotypes. Human studies suggest that propionate has overall anti-obesity effects due to its well-documented chemistry, cellular signaling mechanisms, and various clinical benefits. Butyrate, similar to propionate, has the ability to reduce obesity by stimulating the release of appetite-suppressing hormones and promoting the synthesis of leptin. Tryptophan affects systemic hormone secretion, with indole stimulating the release of GLP-1, which impacts insulin secretion, appetite suppression, and gastric emptying. Bile acids, synthesized from cholesterol in the liver and subsequently modified by gut bacteria, play an essential role in the digestion and absorption of dietary fats and fat-soluble vitamins, but they also interact directly with intestinal microbiota and their metabolites. One study using statistical methods identified primarily two groupings of enterotypes Bacteroides and Ruminococcus. The Prevotella-dominated enterotype, P-type, in humans correlates with vegetarians, high-fiber and carbohydrate-rich diets, and traditional diets. Conversely, individuals who consume diets rich in animal fats and proteins, typical in Western-style diets, often exhibit the Bacteroides-dominated, B-type, enterotype. The P-type showcases efficient hydrolytic enzymes for plant fiber degradation but has limited lipid and protein fermentation capacity. Conversely, the B-type features specialized enzymes tailored for the degradation of animal-derived carbohydrates and proteins, showcasing an enhanced saccharolytic and proteolytic potential. Generally, models excel at predictions but often struggle to fully elucidate why certain substances yield varied responses. These studies provide valuable insights into the potential for personalized dietary recommendations based on enterotypes.

Fecal microbiota transplantation: Emerging applications in autoimmune diseases

Both genetic susceptibility and environmental factors are important contributors to autoimmune disease pathogenesis. As an environmental factor, the gut microbiome plays a crucial role in the development and progression of autoimmune diseases. Thus, strategies targeting gut microbiome alterations can potentially be used to treat autoimmune disease. Microbiota-based interventions, such as prebiotics, probiotics, dietary interventions, and fecal microbiota transplantation (FMT), have attracted growing interest as novel treatment approaches. FMT is an effective method for treating recurrent Clostridioides difficile infections; moreover, it is emerging as a promising treatment for patients with inflammatory bowel disease and other autoimmune diseases. Although the mechanisms underpinning the interaction between the gut microbiome and host are not fully understood in patients with autoimmune disease, FMT has been shown to restore altered gut microbiota composition, rebuild the intestinal microecosystem, and mediate innate and adaptive immune responses to achieve a therapeutic effect. In this review, we provide an overview of FMT and discuss how FMT can be used as a novel treatment approach for autoimmune diseases. Furthermore, we discuss recent challenges and offer future research directions.

Emerging technologies in adipose tissue research

Technologies are transforming the understanding of adipose tissue as a complex and dynamic tissue that plays a critical role in energy homoeostasis and metabolic health. This mini-review provides a brief overview of the potential impact of novel technologies in biomedical research and aims to identify areas where these technologies can make the most significant contribution to adipose tissue research. It discusses the impact of cutting-edge technologies such as single-cell sequencing, multi-omics analyses, spatial transcriptomics, live imaging, 3D tissue engineering, microbiome analysis, in vivo imaging, and artificial intelligence/machine learning. As these technologies continue to evolve, we can expect them to play an increasingly important role in advancing our understanding of adipose tissue and improving the treatment of related diseases.

GENERALIZED MATRIX DECOMPOSITION REGRESSION: ESTIMATION AND INFERENCE FOR TWO-WAY STRUCTURED DATA

Motivated by emerging applications in ecology, microbiology, and neuroscience, this paper studies high-dimensional regression with two-way structured data. To estimate the high-dimensional coefficient vector, we propose the generalized matrix decomposition regression (GMDR) to efficiently leverage auxiliary information on row and column structures. GMDR extends the principal component regression (PCR) to two-way structured data, but unlike PCR, GMDR selects the components that are most predictive of the outcome, leading to more accurate prediction. For inference on regression coefficients of individual variables, we propose the generalized matrix decomposition inference (GMDI), a general high-dimensional inferential framework for a large family of estimators that include the proposed GMDR estimator. GMDI provides more flexibility for incorporating relevant auxiliary row and column structures. As a result, GMDI does not require the true regression coefficients to be sparse, but constrains the coordinate system representing the regression coefficients according to the column structure. GMDI also allows dependent and heteroscedastic observations. We study the theoretical properties of GMDI in terms of both the type-I error rate and power and demonstrate the effectiveness of GMDR and GMDI in simulation studies and an application to human microbiome data.

Gut Microbiota and Its Role in the Brain-Gut-Kidney Axis in Hypertension

PURPOSE OF REVIEW

The role of the gut microbiota in modulating blood pressure is increasingly being recognized, currently. The purpose of this review is to summarize recent findings about the mechanisms involved in hypertension with regard to the phenomenon of "gut dysbiosis."

RECENT FINDINGS

Gut dysbiosis, i.e., the imbalance between the gut microbiota and the host, is characterized by a disruption of the tight junction proteins, such as occludins, claudins, and JAMs (junctional adhesion molecules), resulting in increased gut permeability or the so called "leaky gut." Due to the influence of genetic as well as environmental factors, various metabolites produced by the gut microbiota, such as indole and p-cresol, are increased. Thereby, uremic toxins, such as indoxyl sulfates and p-cresol sulfates, accumulate in the blood and the urine, causing damage in the podocytes and the tubular cells. In addition, immunological mechanisms are implicated as well. In particular, a switch from M2 macrophages to M1 macrophages, which produce pro-inflammatory cytokines, occurs. Moreover, a higher level of Th17 cells, releasing large amounts of interleukin-17 (IL-17), has been reported, when a diet rich in salt is consumed. Therefore, apart from the aggravation of uremic toxins, which may account for direct harmful effects on the kidney, there is inflammation not only in the gut, but in the kidneys as well. This crosstalk between the gut and the kidney is suggested to play a crucial role in hypertension. Notably, the brain is also implicated, with an increasing sympathetic output. The brain-gut-kidney axis seems to be deeply involved in the development of hypertension and chronic kidney disease (CKD). The notion that, by modulating the gut microbiota, we could regulate blood pressure is strongly supported by the current evidence. A healthy diet, low in animal protein and fat, and low in salt, together with the utilization of probiotics, prebiotics, synbiotics, or postbiotics, may contribute to our fight against hypertension.

Higher Bifidobacterium spp. fecal abundance is associated with a lower prevalence of hyperglycemia and cardiovascular risk markers among schoolchildren from Bahia, Brazil

The gut microbiome has recently been the subject of considerable scientific interest due to its essential bodily functions. Several factors can change the composition and function of the gut microbiome, and dietary habits are one of the most important contributors. Despite the recognition of the probiotic effects related to the genus Bifidobacterium spp. (BIF) studies aiming to assess its relationship with metabolic outcomes show conflicting results, particularly in the child population. This cross-sectional study aimed to evaluate the fecal abundance of BIF in a group of schoolchildren from public schools in Bahia, Brazil, and to investigate their relationship with food consumption and laboratory and anthropometric characteristics. A sample of 190 subjects aged 5 to 19y was randomly selected for dietary, laboratory, and anthropometric assessment. Fecal BIF abundance assessment was performed using the Real-Time Polymerase Chain Reaction assay. Fecal BIF abundance was higher among subjects who had lower intakes of meat. The abundance of BIF was also higher among subjects with lower Waist Circumference and Waist-to-Height Ratio (WHtR). Low BIF abundance was associated with a higher prevalence of hyperglycemia (PR 1.04, 95%CI 1.02-1.07, p = 0.001) and high WHtR (PR 1.04, 95%CI 1.01-1, 08, p = 0.015). These findings allow us to conclude that BIF fecal abundance is related to dietary and anthropometric parameters in schoolchildren, and its increase is associated with positive metabolic outcomes.

The Association of Biomolecular Resource Facilities Proteome Informatics Research Group Study on Metaproteomics (iPRG-2020)

Metaproteomics research using mass spectrometry data has emerged as a powerful strategy to understand the mechanisms underlying microbiome dynamics and the interaction of microbiomes with their immediate environment. Recent advances in sample preparation, data acquisition, and bioinformatics workflows have greatly contributed to progress in this field. In 2020, the Association of Biomolecular Research Facilities Proteome Informatics Research Group launched a collaborative study to assess the bioinformatics options available for metaproteomics research. The study was conducted in 2 phases. In the first phase, participants were provided with mass spectrometry data files and were asked to identify the taxonomic composition and relative taxa abundances in the samples without supplying any protein sequence databases. The most challenging question asked of the participants was to postulate the nature of any biological phenomena that may have taken place in the samples, such as interactions among taxonomic species. In the second phase, participants were provided a protein sequence database composed of the species present in the sample and were asked to answer the same set of questions as for phase 1. In this report, we summarize the data processing methods and tools used by participants, including database searching and software tools used for taxonomic and functional analysis. This study provides insights into the status of metaproteomics bioinformatics in participating laboratories and core facilities.

Changes in Hemolymph Microbiota of Chinese Mitten Crab (Eriocheir sinensis) in Response to Aeromonas hydrophila or Staphylococcus aureus Infection

The Chinese mitten crab (Eriocheir sinensis) has significant economic potential in both the Chinese domestic and global markets. The hemolymph microbiota is known to play a critical role in regulating physiological and biochemical functions in crustaceans. However, the study of the hemolymph microbiota of E. sinensis in response to infections has not been undertaken. In this study, changes in the composition and function of the hemolymph microbiota in E. sinensis infected with either Staphylococcus aureus (Sa) or Aeromonas hydrophila (Ah) were investigated using 16S rRNA sequencing, with a phosphate buffer saline (PBS) injection serving as the control. Results showed that the dominant hemolymph microbiota of E. sinensis were Proteobacteria, Bacteroidota, and Firmicutes. The relative abundance of the phyla Firmicutes, Bdellovibrionota, and Myxococcota was significantly reduced in both Sa and Ah groups compared to the PBS group. At the genus level, compared to the PBS group, a significant increase in the abundance of Flavobacterium and Aeromonas was found in both Ah and Sa groups. The analysis of the functional profile showed that pathways related to 'cell growth and death', 'metabolism of terpenoids and polyketides', 'cancers', 'lipid metabolism', 'neurodegenerative diseases', 'metabolism of other amino acids', 'xenobiotics biodegradation and metabolism', and 'circulatory system and endocrine system' were predominant in the Ah group. Meanwhile, pathways related to 'metabolism or genetic information progressing', such as 'translation', 'metabolic diseases', and 'cellular processes and signaling', were enriched in the Sa group. This study revealed the effects of pathogens (S. aureus or A. hydrophila) on the maintenance of the hemolymph microbiota in E. sinensis. It shed light on the mechanisms employed by the hemolymph microbiota of E. sinensis under pathogen stimulation.

Integrated multi-omics analyses of microbial communities: a review of the current state and future directions

Integrated multi-omics analyses of microbiomes have become increasingly common in recent years as the emerging omics technologies provide an unprecedented opportunity to better understand the structural and functional properties of microbial communities. Consequently, there is a growing need for and interest in the concepts, approaches, considerations, and available tools for investigating diverse environmental and host-associated microbial communities in an integrative manner. In this review, we first provide a general overview of each omics analysis type, including a brief history, typical workflow, primary applications, strengths, and limitations. Then, we inform on both experimental design and bioinformatics analysis considerations in integrated multi-omics analyses, elaborate on the current approaches and commonly used tools, and highlight the current challenges. Finally, we discuss the expected key advances, emerging trends, potential implications on various fields from human health to biotechnology, and future directions.

Unraveling the Gut Microbiome-Diet Connection: Exploring the Impact of Digital Precision and Personalized Nutrition on Microbiota Composition and Host Physiology

The human gut microbiome, an intricate ecosystem housing trillions of microorganisms within the gastrointestinal tract, holds significant importance in human health and the development of diseases. Recent advances in technology have allowed for an in-depth exploration of the gut microbiome, shedding light on its composition and functions. Of particular interest is the role of diet in shaping the gut microbiome, influencing its diversity, population size, and metabolic functions. Precision nutrition, a personalized approach based on individual characteristics, has shown promise in directly impacting the composition of the gut microbiome. However, to fully understand the long-term effects of specific diets and food components on the gut microbiome and to identify the variations between individuals, longitudinal studies are crucial. Additionally, precise methods for collecting dietary data, alongside the application of machine learning techniques, hold immense potential in comprehending the gut microbiome's response to diet and providing tailored lifestyle recommendations. In this study, we investigated the complex mechanisms that govern the diverse impacts of nutrients and specific foods on the equilibrium and functioning of the individual gut microbiome of seven volunteers (four females and three males) with an average age of 40.9 ± 10.3 years, aiming at identifying potential therapeutic targets, thus making valuable contributions to the field of personalized nutrition. These findings have the potential to revolutionize the development of highly effective strategies that are tailored to individual requirements for the management and treatment of various diseases.

Guidelines for microbiome studies in renal physiology

Gut microbiome research has increased dramatically in the last decade, including in renal health and disease. The field is moving from experiments showing mere association to causation using both forward and reverse microbiome approaches, leveraging tools such as germ-free animals, treatment with antibiotics, and fecal microbiota transplantations. However, we are still seeing a gap between discovery and translation that needs to be addressed, so that patients can benefit from microbiome-based therapies. In this guideline paper, we discuss the key considerations that affect the gut microbiome of animals and clinical studies assessing renal function, many of which are often overlooked, resulting in false-positive results. For animal studies, these include suppliers, acclimatization, baseline microbiota and its normalization, littermates and cohort/cage effects, diet, sex differences, age, circadian differences, antibiotics and sweeteners, and models used. Clinical studies have some unique considerations, which include sampling, gut transit time, dietary records, medication, and renal phenotypes. We provide best-practice guidance on sampling, storage, DNA extraction, and methods for microbial DNA sequencing (both 16S rRNA and shotgun metagenome). Finally, we discuss follow-up analyses, including tools available, metrics, and their interpretation, and the key challenges ahead in the microbiome field. By standardizing study designs, methods, and reporting, we will accelerate the findings from discovery to translation and result in new microbiome-based therapies that may improve renal health.

The Y-ome Conundrum: Insights into Uncharacterized Genes and Approaches for Functional Annotation

The ever-increasing availability of genome sequencing data has revealed a substantial number of uncharacterized genes without known functions across various organisms. The first comprehensive genome sequencing of E. coli K12 revealed that more than 50% of its open reading frames corresponded to transcripts with no known functions. The group of protein-coding genes without a functional description and/or a recognized pathway, beginning with the letter "Y", is classified as the "y-ome". Several efforts have been made to elucidate the functions of these genes and to recognize their role in biological processes. This review provides a brief update on various strategies employed when studying the y-ome, such as high-throughput experimental approaches, comparative omics, metabolic engineering, gene expression analysis, and data integration techniques. Additionally, we highlight recent advancements in functional annotation methods, including the use of machine learning, network analysis, and functional genomics approaches. Novel approaches are required to produce more precise functional annotations across the genome to reduce the number of genes with unknown functions.

Genetic Engineering of Resident Bacteria in the Gut Microbiome

Techniques by which to genetically manipulate members of the microbiota enable both the evaluation of host-microbe interactions and an avenue by which to monitor and modulate human physiology. Genetic engineering applications have traditionally focused on model gut residents, such as Escherichia coli and lactic acid bacteria. However, emerging efforts by which to develop synthetic biology toolsets for "nonmodel" resident gut microbes could provide an improved foundation for microbiome engineering. As genome engineering tools come online, so too have novel applications for engineered gut microbes. Engineered resident gut bacteria facilitate investigations of the roles of microbes and their metabolites on host health and allow for potential live microbial biotherapeutics. Due to the rapid pace of discovery in this burgeoning field, this minireview highlights advancements in the genetic engineering of all resident gut microbes.

Integrating Omics Data in Genome-Scale Metabolic Modeling: A Methodological Perspective for Precision Medicine

Recent advancements in omics technologies have generated a wealth of biological data. Integrating these data within mathematical models is essential to fully leverage their potential. Genome-scale metabolic models (GEMs) provide a robust framework for studying complex biological systems. GEMs have significantly contributed to our understanding of human metabolism, including the intrinsic relationship between the gut microbiome and the host metabolism. In this review, we highlight the contributions of GEMs and discuss the critical challenges that must be overcome to ensure their reproducibility and enhance their prediction accuracy, particularly in the context of precision medicine. We also explore the role of machine learning in addressing these challenges within GEMs. The integration of omics data with GEMs has the potential to lead to new insights, and to advance our understanding of molecular mechanisms in human health and disease.

A bibliometric analysis of the global impact of metaproteomics research

Background

Metaproteomics is a subfield in meta-omics that is used to characterize the proteome of a microbial community. Despite its importance and the plethora of publications in different research area, scientists struggle to fully comprehend its functional impact on the study of microbiomes. In this study, bibliometric analyses are used to evaluate the current state of metaproteomic research globally as well as evaluate the specific contribution of Africa to this burgeoning research area. In this study, we use bibliometric analyses to evaluate the current state of metaproteomic research globally, identify research frontiers and hotspots, and further predict future trends in metaproteomics. The specific contribution of Africa to this research area was evaluated.

Methods

Relevant documents from 2004 to 2022 were extracted from the Scopus database. The documents were subjected to bibliometric analyses and visualization using VOS viewer and Biblioshiny package in R. Factors such as the trends in publication, country and institutional cooperation networks, leading scientific journals, author's productivity, and keywords analyses were conducted. The African publications were ranked using Field-Weighted Citation Impact (FWCI) scores.

Results

A total of 1,138 documents were included and the number of publications increased drastically from 2004 to 2022 with more publications (170) reported in 2021. In terms of publishers, Frontiers in Microbiology had the highest number of total publications (62). The United States of America (USA), Germany, China, and Canada, together with other European countries were the most productive. Institution-wise, the Helmholtz Zentrum für Umweltforschung, Germany had more publications while Max Plank Institute had the highest total collaborative link strength. Jehmlich N. was the most productive author whereas Hettich RL had the highest h-index of 63. Regarding Africa, only 2.2% of the overall publications were from the continent with more publication outputs from South Africa. More than half of the publications from the continent had an FWCI score ≥ 1.

Conclusion

The scientific outputs of metaproteomics are rapidly evolving with developed countries leading the way. Although Africa showed prospects for future progress, this could only be accelerated by providing funding, increased collaborations, and mentorship programs.

Diagnostic approaches for dengue infection

INTRODUCTION

Every year, a significant rise in dengue incidence observed is responsible for 10% of fever episodes in children and adolescents in endemic countries. Considering that the symptoms of dengue are similar to those of many other viruses, early diagnosis of the disease has long been difficult, and lack of sensitive diagnostic tools may be another factor contributing to a rise in dengue incidence.

AREAS COVERED

This review will highlight dengue diagnostics strategies and discuss other possible targets for dengue diagnosis. Understanding the dynamics of the immune response and how it affects viral infection has enabled informed diagnosis. As more technologies emerge, precise assays that include some clinical markers need to be included.

EXPERT OPINION

Future diagnostic strategies will require the use both viral and clinical markers in a serial manner with the use of artificial intelligence technology to determine from the first point of illness to better determine severity status and management. A definitive endpoint is not in the horizon as the disease as well as the virus is constantly evolving and hence many developed assays need to be constantly changing some of their reagents periodically as newer genotypes and probably too serotypes emerge.

Multi-omics in Crohn's disease: New insights from inside

Crohn's disease (CD) is an inflammatory bowel disease (IBD) with complex clinical manifestations such as chronic diarrhea, weight loss and hematochezia. Despite the increasing incidence worldwide, cure of CD remains extremely difficult. The rapid development of high-throughput sequencing technology with integrated-omics analyses in recent years has provided a new means for exploring the pathogenesis, mining the biomarkers and designing targeted personalized therapeutics of CD. Host genomics and epigenomics unveil heredity-related mechanisms of susceptible individuals, while microbiome and metabolomics map host-microbe interactions in CD patients. Proteomics shows great potential in searching for promising biomarkers. Nonetheless, single omics technology cannot holistically connect the mechanisms with heterogeneity of pathological behavior in CD. The rise of multi-omics analysis integrates genetic/epigenetic profiles with protein/microbial metabolite functionality, providing new hope for comprehensive and in-depth exploration of CD. Herein, we emphasized the different omics features and applications of CD and discussed the current research and limitations of multi-omics in CD. This review will update and deepen our understanding of CD from integration of broad omics spectra and will provide new evidence for targeted individualized therapeutics.

Gut Microbes Meet Machine Learning: The Next Step towards Advancing Our Understanding of the Gut Microbiome in Health and Disease

The human gut microbiome plays a crucial role in human health and has been a focus of increasing research in recent years. Omics-based methods, such as metagenomics, metatranscriptomics, and metabolomics, are commonly used to study the gut microbiome because they provide high-throughput and high-resolution data. The vast amount of data generated by these methods has led to the development of computational methods for data processing and analysis, with machine learning becoming a powerful and widely used tool in this field. Despite the promising results of machine learning-based approaches for analyzing the association between microbiota and disease, there are several unmet challenges. Small sample sizes, disproportionate label distribution, inconsistent experimental protocols, or a lack of access to relevant metadata can all contribute to a lack of reproducibility and translational application into everyday clinical practice. These pitfalls can lead to false models, resulting in misinterpretation biases for microbe–disease correlations. Recent efforts to address these challenges include the construction of human gut microbiota data repositories, improved data transparency guidelines, and more accessible machine learning frameworks; implementation of these efforts has facilitated a shift in the field from observational association studies to experimental causal inference and clinical intervention.

The microbiome as a major function of the gastrointestinal tract and its implication in micronutrient metabolism and chronic diseases

The composition and function of microbes harbored in the human gastrointestinal lumen have been underestimated for centuries because of the underdevelopment of nucleotide sequencing techniques and the lack of humanized gnotobiotic models. Now, we appreciate that the gut microbiome is an integral part of the human body and exerts considerable roles in host health and diseases. Dietary factors can induce changes in the microbial community composition, metabolism, and function, thereby altering the host immune response, and consequently, may influence disease risks. An imbalance of gut microbiome homeostasis (i.e., dysbiosis) has been linked to several chronic diseases, such as inflammatory bowel diseases, obesity, and diabetes. Remarkable progress has recently been made in better understanding the extent to which the influence of the diet-microbiota interaction on host health outcomes in both animal models and human participants. However, the exact causality of the gut microbiome on the development of diseases is still controversial. In this review, we will briefly describe the general structure and function of the intestine and the process of nutrient absorption in humans. This is followed by a summarization of the recent updates on interactions between gut microbiota and individual micronutrients, including carotenoids, vitamin A, vitamin D, vitamin C, folate, iron, and zinc. In the opinion of the authors, these nutrients were identified as representative of vitamins and minerals with sufficient research on their roles in the microbiome. The host responses to the gut microbiome will also be discussed. Future direction in microbiome research, for example, precision microbiome, will be proposed.

The gut microbiome and hypertension

A large body of evidence has emerged in the past decade supporting a role for the gut microbiome in the regulation of blood pressure. The field has moved from association to causation in the last 5 years, with studies that have used germ-free animals, antibiotic treatments and direct supplementation with microbial metabolites. The gut microbiome can regulate blood pressure through several mechanisms, including through gut dysbiosis-induced changes in microbiome-associated gene pathways in the host. Microbiota-derived metabolites are either beneficial (for example, short-chain fatty acids and indole-3-lactic acid) or detrimental (for example, trimethylamine N-oxide), and can activate several downstream signalling pathways via G protein-coupled receptors or through direct immune cell activation. Moreover, dysbiosis-associated breakdown of the gut epithelial barrier can elicit systemic inflammation and disrupt intestinal mechanotransduction. These alterations activate mechanisms that are traditionally associated with blood pressure regulation, such as the renin-angiotensin-aldosterone system, the autonomic nervous system, and the immune system. Several methodological and technological challenges remain in gut microbiome research, and the solutions involve minimizing confounding factors, establishing causality and acting globally to improve sample diversity. New clinical trials, precision microbiome medicine and computational methods such as Mendelian randomization have the potential to enable leveraging of the microbiome for translational applications to lower blood pressure.

Cepharanthine Alleviates DSS-Induced Ulcerative Colitis via Regulating Aconitate Decarboxylase 1 Expression and Macrophage Infiltration

Cepharanthine (CEP), a bisbenzylisoquinoline alkaloid from tubers of Stephania, protects against some inflammatory diseases. Aconitate decarboxylase 1 (ACOD1) is also known as immune-responsive gene 1 (IRG1), which plays an important immunometabolism role in inflammatory diseases by mediating the production of itaconic acid. ACOD1 exhibits abnormal expression in ulcerative colitis (UC). However, whether CEP can combat UC by affecting ACOD1 expression remains unanswered. This study was designed to explore the protective effects and mechanisms of CEP in treating colitis through in vitro and in vivo experiments. In vitro assays indicated that CEP inhibited LPS-induced secretion of pro-inflammatory cytokines and ACOD1 expression in RAW264.7 macrophages. Additionally, in the mouse model of DSS-induced colitis, CEP decreased macrophage infiltration and ACOD1 expression in colon tissue. After treatment with antibiotics (Abx), the expression of ACOD1 changed with the composition of gut microbiota. Correlation analysis also revealed that Family-XIII-AD3011-group and Rumini-clostridium-6 were positively correlated with ACOD1 expression level. Additionally, data of the integrative Human Microbiome Project (iHMP) showed that ACOD1 was highly expressed in the colon tissue of UC patients and this expression was positively correlated with the severity of intestinal inflammation. Collectively, CEP can counter UC by modulating gut microbiota and inhibiting the expression of ACOD1. CEP may serve as a potential pharmaceutical candidate in the treatment of UC.

Microbiota-directed biotherapeutics: considerations for quality and functional assessment

Mounting evidence points to causative or correlative roles of gut microbiome in the development of a myriad of diseases ranging from gastrointestinal diseases, metabolic diseases to neurological disorders and cancers. Consequently, efforts have been made to develop and apply therapeutics targeting the human microbiome, in particular the gut microbiota, for treating diseases and maintaining wellness. Here we summarize the current development of gut microbiota-directed therapeutics with a focus on novel biotherapeutics, elaborate the need of advanced -omics approaches for evaluating the microbiota-type biotherapeutics, and discuss the clinical and regulatory challenges. We also discuss the development and potential application of ex vivo microbiome assays and in vitro intestinal cellular models in this context. Altogether, this review aims to provide a broad view of promises and challenges of the emerging field of microbiome-directed human healthcare.

Gut Microbiome Analysis for Personalized Nutrition: The State of Science

Whereas most concepts of personalized nutrition (PN) in the past, included genotyping, recent years have brought new approaches that include microbiome analysis to optimize recommendations for diet and lifestyle changes. The new approach, offered by companies, that microbiome analysis provides a real benefit to either more concise recommendations or for increased compliance to PN, is largely lacking scientific validation. Although the microbiome field shows enormous proliferation, it has some major flaws that make its use in the public health domain currently critical. Starting with the quality and representative character of the stool samples, its processing and analysis as well as assembly of metagenome data and the interpretation. Moreover, there is still no consensus of what constitutes a "normal/healthy" microbiome, nor what features characterize a dysbiotic microbiome. And, based on hundreds of individual parameters and environmental factors, the intestinal microbiome shows a huge variability and consequently changing one factor-such as food intake-is likely to have a limited impact in achieving optimized health. The present review intends to summarize the state of consolidated knowledge on human gut microbiome in the context of diet and disease, its key features, and its influencing factors as well as its "add-on" quality for PN offers.

Gut Microbiota Alterations and Primary Glomerulonephritis in Children: A Review

The article summarizes the current evidence on the impact of microbiota alterations on immune-mediated primary glomerulonephritis in children. In particular, the focus is on the link between dysbiosis and the onset or recurrence of idiopathic nephrotic syndrome, immunoglobulin A nephropathy, and membranous nephropathy. The aim is to describe possible pathomechanisms, differences in gut microbiota composition between pediatric patients and healthy controls, and possible usage of microbiota manipulations in supportive therapy. On this basis, we attempt to indicate directions for further research in that field.

Interdisciplinary Overview of Lipopeptide and Protein-Containing Biosurfactants

Biosurfactants are amphipathic molecules capable of lowering interfacial and superficial tensions. Produced by living organisms, these compounds act the same as chemical surfactants but with a series of improvements, the most notable being biodegradability. Biosurfactants have a wide diversity of categories. Within these, lipopeptides are some of the more abundant and widely known. Protein-containing biosurfactants are much less studied and could be an interesting and valuable alternative. The harsh temperature, pH, and salinity conditions that target organisms can sustain need to be understood for better implementation. Here, we will explore biotechnological applications via lipopeptide and protein-containing biosurfactants. Also, we discuss their natural role and the organisms that produce them, taking a glimpse into the possibilities of research via meta-omics and machine learning.

Pharmacomicrobiomics in Anticancer Therapies: Why the Gut Microbiota Should Be Pointed Out

Anticancer treatments have shown a variable therapeutic outcome that may be partly attributable to the activity of the gut microbiota on the pathology and/or therapies. In recent years, microbiota-drug interactions have been extensively investigated, but most of the underlying molecular mechanisms still remain unclear. In this review, we discuss the relationship between the gut microbiota and some of the most commonly used drugs in oncological diseases. Different strategies for manipulating the gut microbiota layout (i.e., prebiotics, probiotics, antibiotics, and fecal microbiota transplantation) are then explored in order to optimize clinical outcomes in cancer patients. Anticancer technologies that exploit tumor-associated bacteria to target tumors and biotransform drugs are also briefly discussed. In the field of pharmacomicrobiomics, multi-omics strategies coupled with machine and deep learning are urgently needed to bring to light the interaction among gut microbiota, drugs, and host for the development of truly personalized precision therapies.